📌 Core Information
🔹 Job Title: AI Content Expert II, AGI Data Services
🔹 Company: Amazon
🔹 Location: Boston, Massachusetts, United States
🔹 Job Type: On-site
🔹 Category: AI & Machine Learning
🔹 Date Posted: April 24, 2025
🔹 Experience Level: 2-5 years
🔹 Remote Status: On-site
🚀 Job Overview
Key aspects of this role include:
- Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content
- Writing grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines
- Performing audits and quality checks of tasks completed by other specialists, if required
- Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks
ASSUMPTION: This role requires a strong attention to detail, excellent writing skills, and the ability to work independently with minimal supervision.
📋 Key Responsibilities
✅ Create and annotate high-quality complex training data in multiple modalities on various topics, including technical or science-related content
✅ Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines
✅ Perform audits and quality checks of tasks completed by other specialists, if required
✅ Make sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks
✅ Dive deep into issues and implement solutions independently
✅ Identify and report tooling bugs and suggest improvements
ASSUMPTION: This role may require occasional overtime or working on weekends to meet project deadlines.
🎯 Required Qualifications
Education: Bachelor's degree in Linguistics, English, Computer Science, or a related field
Experience: 2-5 years of experience in data annotation, content creation, or a related field
Required Skills:
- Excellent written and verbal communication skills in English
- Strong attention to detail and ability to maintain high-quality standards
- Ability to work independently and make sound judgments in ambiguous situations
- Familiarity with data annotation tools and processes
- Basic understanding of machine learning and AI concepts
Preferred Skills:
- Experience with AGI's Large Language Models (LLMs)
- Fluency in multiple languages
- Background in technical writing or scientific research
ASSUMPTION: Proficiency in English is required for this role, and fluency in additional languages is a strong plus.
💰 Compensation & Benefits
Salary Range: $70,000 - $110,000 per year (based on industry standards for AI Content Experts with 2-5 years of experience in the Boston area)
Benefits:
- Medical, dental, and vision insurance
- 401(k) matching
- Paid time off (vacation, sick, and holidays)
- Maternity and paternity leave
- Employee discounts on Amazon products
Working Hours: Full-time (40 hours/week), with flexible scheduling and the possibility of working remotely occasionally
ASSUMPTION: The salary range provided is an estimate based on industry standards and may vary depending on the candidate's experience and qualifications.
📌 Applicant Insights
🔍 Company Context
Industry: E-commerce and Technology
Company Size: 10,001+ employees (Large enterprise)
Founded: 1994 (Over 25 years ago)
Company Description:
- Amazon is a multinational technology company that focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence
- Amazon is known for its innovative culture, customer obsession, and commitment to operational excellence
- The company offers a wide range of products and services, including Amazon.com, Amazon Web Services (AWS), Amazon Prime Video, and Amazon Alexa
Company Specialties:
- E-commerce
- Cloud Computing
- Artificial Intelligence
- Digital Streaming
Company Website: https://www.amazon.com
ASSUMPTION: Working at Amazon offers opportunities for professional growth and exposure to cutting-edge technology in a dynamic and innovative environment.
📊 Role Analysis
Career Level: Mid-level (2-5 years of experience)
Reporting Structure: This role reports directly to the Data Team Manager
Work Arrangement: On-site, with the possibility of occasional remote work
Growth Opportunities:
- Advancement to Senior AI Content Expert or related roles
- Expansion into other areas of Amazon's data services or AI teams
- Potential to work on high-impact projects and contribute to the development of Amazon's Large Language Models
ASSUMPTION: This role offers opportunities for career growth and development within Amazon's data services and AI teams.
🌍 Location & Work Environment
Office Type: Corporate office with open-plan workspaces and dedicated team areas
Office Location(s): Boston, Massachusetts, United States
Geographic Context:
- Boston is a major city in the northeastern United States, known for its rich history, culture, and education
- The city offers a diverse range of neighborhoods, with vibrant arts, food, and entertainment scenes
- Boston has a humid continental climate, with warm summers and cold, snowy winters
Work Schedule: Monday-Friday, with flexible hours and the possibility of working remotely occasionally
ASSUMPTION: Working in Boston offers a dynamic and culturally diverse environment, with access to numerous amenities and attractions.
💼 Interview & Application Insights
Typical Process:
- Online application and resume screening
- Phone or video screening with a recruiter
- Technical assessment or take-home assignment
- On-site or virtual interview with the hiring manager and team members
- Final decision and offer
Key Assessment Areas:
- Writing and communication skills
- Attention to detail and quality assurance
- Problem-solving and decision-making abilities
- Familiarity with data annotation tools and processes
Application Tips:
- Highlight relevant experience and skills in your resume, using keywords from the job description
- Tailor your cover letter to explain how your background and skills make you a strong fit for this role
- Prepare for the technical assessment or take-home assignment by reviewing data annotation best practices and familiarizing yourself with Amazon's data services
ATS Keywords: Data annotation, content creation, AI, machine learning, attention to detail, quality assurance, technical writing, problem-solving, decision-making
ASSUMPTION: The application process for this role may take several weeks, and communication from the Amazon recruitment team may be limited.
🛠️ Tools & Technologies
- Amazon Web Services (AWS) platform
- Data annotation tools (e.g., Amazon SageMaker Ground Truth, Labelbox, or similar)
- Microsoft Office Suite or Google Workspace
- Project management tools (e.g., JIRA, Asana, or Trello)
ASSUMPTION: Familiarity with Amazon's suite of tools and platforms is not required but may be helpful for this role.
👔 Cultural Fit Considerations
Company Values:
- Customer obsession
- Ownership
- Invent and simplify
- Learn and be curious
- Hire and develop the best
- Insist on the highest standards
- Think big
- Bias for action
- Frugality
- Earn trust
Work Style:
- Fast-paced and dynamic environment
- Collaborative and team-oriented culture
- Focus on innovation, invention, and continuous improvement
- Results-driven and data-informed decision-making
Self-Assessment Questions:
- Do you thrive in a fast-paced, dynamic environment, and are you comfortable with ambiguity and change?
- Are you passionate about customer-centric design and creating high-quality products and services?
- Do you have a bias for action and a strong desire to learn and be curious?
ASSUMPTION: Amazon's culture is fast-paced, innovative, and customer-focused, with a strong emphasis on continuous learning and improvement.
⚠️ Potential Challenges
- Working with complex and ambiguous data may require significant problem-solving and decision-making
- Occasional overtime or working on weekends may be required to meet project deadlines
- Adapting to Amazon's fast-paced and dynamic work environment may be challenging for some candidates
- Competition for roles within Amazon's data services and AI teams may be high
ASSUMPTION: These challenges are inherent to working in a fast-paced, innovative environment and can be mitigated with strong communication, time management, and adaptability skills.
📈 Similar Roles Comparison
- This role is similar to other AI Content Expert or Data Annotation Specialist positions, but with a focus on Amazon's Large Language Models and data services
- Compared to other AI roles, this position requires strong writing and communication skills, as well as attention to detail and quality assurance
- Career progression in this role may lead to senior AI content expert or related roles within Amazon's data services and AI teams
ASSUMPTION: This role offers unique opportunities to work on cutting-edge AI projects and contribute to the development of Amazon's Large Language Models.
📝 Sample Projects
- Creating and annotating training data for Amazon's Large Language Models, such as Amazon Alexa or Amazon Transcribe
- Developing and implementing quality assurance processes for data annotation tasks
- Collaborating with cross-functional teams to improve data annotation tools and workflows
ASSUMPTION: These sample projects illustrate the diverse and impactful nature of the work performed by AI Content Experts within Amazon's data services and AI teams.
❓ Key Questions to Ask During Interview
- Can you describe the team structure and dynamics of the Data Team?
- How does this role contribute to Amazon's overall mission and strategy for AI and machine learning?
- What are the most challenging aspects of working on Amazon's Large Language Models, and how does this role address them?
- How does Amazon support the professional growth and development of its employees in AI and machine learning roles?
- What is the typical career path for an AI Content Expert within Amazon's data services and AI teams?
ASSUMPTION: Asking these questions demonstrates your interest in the role and provides valuable insights into the work environment and career opportunities.
📌 Next Steps for Applicants
To apply for this position:
- Submit your application through this link
- Tailor your resume to highlight relevant experience and skills, using keywords from the job description
- Write a cover letter explaining how your background and skills make you a strong fit for this role
- Prepare for the technical assessment or take-home assignment by reviewing data annotation best practices and familiarizing yourself with Amazon's data services
- Follow up with the Amazon recruitment team one week after submitting your application, if you have not heard back
⚠️ This job description contains AI-assisted information. Details should be verified directly with the employer before making decisions.
